CV ridge regression plot

[user124578]

Hi

Any ideas why the plot for the ridge regression isn't working correctly. If i plot this using the code below the first dotted line should show the optimal value for lambda. The graph doesn't seem to reflect the min value(optimal value) Any ideas?

x1 and y2 are matrix

ridge_cv_fit = cv.glmnet(x2, y2, alpha=0, standardize=FALSE, lambda=grid)

plot(ridge_cv_fit)

(lambda_ridge_min = ridge_cv_fit$lambda.min)

[FJCC]

Since we cannot see your plot, it is difficult to say what is going on. If you cannot upload a Reproducible Example, as explained in the link below, can you at least post an image of the plot?

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…